DDoS Attack Detection Using Moment in Statistics with Discriminant Analysis
Journal Title: International Journal of the Computer, the Internet and Management - Year 2017, Vol 25, Issue 1
Abstract
The research objectives are to create discriminant analysis functions using moment of aggregate traffic packets on victims to classifying attack situations and detect DDoS attacks on the network. To simulate the network model, the DDoS attack simulation model over wired networks was conducted to keep data packets from the victim and then analyze to find the attributes from the attack. In order to achieve a more accurate classification, discriminant analysis was used to find the characteristics of harmful traffic. In this research, the discriminant analysis function was created by using four moments of the traffic. Accurately detection was found to at 92.5%.
Authors and Affiliations
Pradit Pitaksathienkul, Pongpisit Wuttidittachotti
Keywords
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